Changes in microbiome composition after fecal microbiota transplantation via oral gavage and magnetic navigation technology-assisted proximal colon/cecum enema in antibiotic knock-down rats: a comparative experimental study

Abstract

Background: Fecal microbiota transplantation (FMT) transfers fecal matter from a donor into the gastrointestinal tract of a recipient to induce changes to the gut microbiota for therapeutic benefit; however, differences in the composition of gut microbiota after FMT via different donor material delivery routes are poorly understood. In this study, we first developed a novel technique for FMT, magnetic navigation technology(MAT)-assisted proximal colon enemas, in healthy Sprague-Dawley rats. Besides, the difference in fecal microbiota composition after FMT via oral gavage and proximal colon/cecum enemas was determined in antibiotic knock-down rats, in addition to the impact on intestinal barrier function.

Methods: A device consisting of an external magnet and a magnet-tipped 6 Fr tube was used in the MAT group (n = 6), and the control group (n = 6) where fecal matter was delivered without magnetic navigation. The feasibility and safety of this method were assessed by angiography and histology. Next, the fecal microbiota of donor rats was transplanted into antibiotic knock-down rats via oral gavage (n = 6) and MAT-assisted proximal colon/cecum enema (n = 6) for a week. Analysis of fecal 16 S rRNA was conducted to determine differences in the composition of gut microbiota between different groups. The rat intestinal barrier integrity were evaulated by H&E and ZO-1/MUC2 immunofluorescence staining.

Results: The end of the fecal tube could be placed in the cecum or proximal colon of rats in MAT group; however, this was rarely achieved in the control group. No colon perforation or bleeding was detected in either group. After fecal microbiota transplantation, the microbiota α-diversity and β-diversity were comparable among the different delivery routes.At the family level, the relative abundances of Muribaculaceae, Oscillospiraceae, and Erysipelotrichaceae were higher in the gavage treatment group, whereas Lactobacillaceae and Saccharimonadaceae were higher in the enema treatment group (all p < 0.05). FMT by enema was superior to gavage in maintaining the integrity of the rat intestinal barrier, as assessed by an elevation in the density of goblet cells and increased expression of mucin-2.

Conclusions: Fecal microbiota tube placement using magnetic navigation was safe and feasible in rats.Different delivery route for FMT affects the gut microbiota composition and the integrity of the rat intestinal barrier. Future experimental designs should consider the colonization outcomes of critical microbial taxa to determine the optimal FMT delivery routes in scientific research as well as clinical practise.

Keywords: Antibiotic knock-down rat; Delivery route; Fecal microbiota transplantation; Gut microbiota composition.

Fig. 1

The effectiveness and safety of MAT-assisted FMT tube placement in rats. (a) Magnetic device and operation process. (b) External magnets and fecal microbiota transplantation tube with internal magnets at the ends. (c) Fecal microbiota transplantation tube placement using a magnetic navigation technique in rats. (d) Positioning the FMT tube end using radiography. (e) Gross appearances of the colon and cecum after FMT tube placement. (f) Histology of different parts of the colon and cecum after FMT tube placement

Fig. 2

Schema of the experimental design. (a) MAT-assisted FMT tube placement. (b) No MAT-assisted FMT tube placement. (c) Design scheme for studying the differences in the composition of gut microbiota after FMT via different donor material delivery routes

Fig. 3

Diversity analysis of the gut microbiome. (a) ASV numbers. (b) Venn graph. (c) ACE index of α diversities analysis. (d) Shannon index of α diversities analysis. (e) PCoA analyses. (f) Anosim analysis. Data are expressed as means ± SEM (n = 6)

Fig. 4

The composition of the gut microbiome after FMT in rats among three groups. (a) Relative abundance distribution at the phylum level among three groups. (b) Relative abundance distribution in the Gavage and Enema group at the phylum level. (c) A bar graph of the phylum distribution with a TOP 5 abundance. (d) Relative abundance distribution at the family level among three groups. (e) Relative abundance distribution at family levels in the Gavage and Enema groups at the phylum level. (f) A bar graph of family distribution with statistical differences between the Gavage and Enema groups. Data are expressed as means ± SEM (n = 6)

Fig. 5

Lefse branch plot. (a) Histogram of distribution of linear discriminant analysis values revealing the microbiome of different taxa among the three groups. (b) The different bacterial-rich taxa among the three groups. Green, orange, and blue show different bacterial taxa in the Gavage, Enema, and ABx groups, respectively, and yellow shows no significant differences between groups

Fig. 6

Prediction of the BugBase phenotype in the Gavage and Enema groups. (a) Aerobic, (b) Anaerobic, (c) Containing mobile elements, (d) Facultatively anaerobic, (e) Forming biofilms, (f) Gram-negative, (g) Gram-positive, (h) Potentially pathogenic, (i) Stress-tolerant

Fig. 7

Comparison of intestinal barriers in different groups. (a) Alcian blue staining of the colon (scale bar, 50 μm), (b) Representative immuno-fluorescence images of mucin-2 (Muc-2) in the colon (scale bar, 50 μm), (c) Representative immuno-fluorescence images of zonula occluden-1 (Zo-1) in the colon (scale bar, 100 μm), (d) The number of goblet cells in the colon (n = 6), (e) Quantification of Muc-2 protein levels (n = 6), (f) Quantification of Zo-1protein levels (n = 6), (g) Quantification of Muc-2 fluorescence intensity (n = 6), (h) Quantification of Zo-1 fluorescence intensity (n = 6)

Fig. 8

Diversity analysis of the gut microbiome. (a) ASV numbers. (b) Venn graph. (c) ACE index of α diversities analysis. (d) Shannon index of α diversities analysis. (e) PCoA analyses. (f) Anosim analysis. Data are expressed as means ± SEM (n = 6)